#python #cloud #cloud_native #computer_vision #deep_learning #docker #framework #image_search #jina #machine_learning #microservice #neural_search #nlp #pytorch #search #semantic_search #tensorflow #transformers #video_search #zmq

https://github.com/jina-ai/jina

#go #classification #contextual_search #database #deep_learning #deep_search #graphql #knn_search #machine_learning #neural_search #restful_api #search_engine #search_engines #semantic_search #semantic_search_engine #vector_database #vector_search #vector_search_engine #vectors #weaviate

https://github.com/semi-technologies/weaviate

#python #ai #bert #dpr #elasticsearch #information_retrieval #language_model #machine_learning #natural_language_processing #neural_search #nlp #pytorch #question_answering #search_engine #semantic_search #squad #summarization #transfer_learning #transformers

https://github.com/deepset-ai/haystack

#python #dalle #dalle_mega #dalle_mini #generative_art #glid3 #human_in_the_loop #jina #neural_search #openai #swinir

https://github.com/jina-ai/dalle-flow

#python #bert #embedding #ernie #information_extraction #neural_search #nlp #paddlenlp #pretrained_models #question_answering #search_engine #semantic_analysis #sentiment_analysis #seq2seq #transformer #transformers #uie

https://github.com/PaddlePaddle/PaddleNLP

#rust #approximate_nearest_neighbor_search #embeddings_similarity #hnsw #image_search #knn_algorithm #machine_learning #matching #mlops #nearest_neighbor_search #neural_network #neural_search #recommender_system #search #search_engine #search_engines #similarity_search #vector_database #vector_search #vector_search_engine

https://github.com/qdrant/qdrant

#python #cross_modal #data_structures #dataclass #deep_learning #docarray #elasticsearch #graphql #multi_modal #multimodal #nearest_neighbor_search #nested_data #neural_search #protobuf #qdrant #semantic_search #sqlite #unstructured_data #vector_search #weaviate

https://github.com/docarray/docarray

#python #embeddings #information_retrieval #language_model #large_language_models #llm #machine_learning #nearest_neighbor_search #neural_search #nlp #search #search_engine #semantic_search #sentence_embeddings #similarity_search #transformers #txtai #vector_database #vector_search #vector_search_engine

https://github.com/neuml/txtai

#go #approximate_nearest_neighbor_search #generative_search #grpc #hnsw #hybrid_search #image_search #information_retrieval #mlops #nearest_neighbor_search #neural_search #recommender_system #search_engine #semantic_search #semantic_search_engine #similarity_search #vector_database #vector_search #vector_search_engine #vectors #weaviate

Weaviate is a powerful, open-source vector database that uses machine learning to make your data searchable. It's fast, scalable, and flexible, allowing you to vectorize your data at import or upload your own vectors. Weaviate supports various modules for integrating with popular AI services like OpenAI, Cohere, and Hugging Face. It's designed for production use with features like scaling, replication, and security. You can use Weaviate for tasks beyond search, such as recommendations, summarization, and integration with neural search frameworks. It offers APIs in GraphQL, REST, and gRPC and has client libraries for several programming languages. This makes it easy to build applications like chatbots, recommendation systems, and image search tools quickly and efficiently. Joining the Weaviate community provides access to tutorials, demos, blogs, and forums to help you get started and stay updated.

https://github.com/weaviate/weaviate

#python #cloud_native #cncf #deep_learning #docker #fastapi #framework #generative_ai #grpc #jaeger #kubernetes #llmops #machine_learning #microservice #mlops #multimodal #neural_search #opentelemetry #orchestration #pipeline #prometheus

Jina-serve is a tool that helps you build and deploy AI services easily. It supports major machine learning frameworks and allows you to scale your services from local development to production quickly. You can use it to create AI services that communicate via gRPC, HTTP, and WebSockets. It has features like built-in Docker integration, one-click cloud deployment, and support for Kubernetes and Docker Compose, making it easy to manage and scale your AI applications. This makes it simpler for you to focus on the core logic of your AI projects without worrying about the technical details of deployment and scaling.

https://github.com/jina-ai/serve